penguin_svm_recipe <-
recipe(sex ~ bill_length_mm + bill_depth_mm + flipper_length_mm +
body_mass_g, data = penguin_train) |>
step_normalize(all_predictors())
summary(penguin_svm_recipe)# A tibble: 5 × 4
variable type role source
<chr> <list> <chr> <chr>
1 bill_length_mm <chr [2]> predictor original
2 bill_depth_mm <chr [2]> predictor original
3 flipper_length_mm <chr [2]> predictor original
4 body_mass_g <chr [2]> predictor original
5 sex <chr [3]> outcome original